Optimizing crew performance through integration of human resource strategies into planning of construction activities

This thesis aims at improving workforce performance through integration of human resource strategies into planning of construction activities. This goal is studied and implemented through three major phases of planning a construction project. The first phase takes place at the project outset when HR is hired for construction of a building/facility. The second phase concurs at the start of the execution phase when a well-performing crew is selected for construction activities. The last phase occurs on a daily basis when jobs are distributed among members of a crew in the real course of the project. Multi-skilling, safety protection, skill level enhancement, addressing aging problem, and preserving labour rights are the main HR strategies integrated with the project planning practices of this thesis. On-the-job training of human resource, activating indolent potential of detailed and individualized data, and combining theory and practice are three pillars which the presented research is built upon. The proposed planning frameworks are devised by investing in young inexperienced workers who have the highest on-the-job learning capacity. The proposed frameworks use learning theory, cognitive load theory, and notion of brain resources to model performance of workers under different HR strategies. These theories integrate HR strategies with project planning practices in which technical and contractual requirements of construction activities, such as quality, time, and budget constraints are taken into account. The proposed frameworks use detailed and classified data imported from different databases, including historical performance records, contractual and regulatory data sources, HR information systems, and Building Information Models (BIM). Such information is then utilized in algorithms developed for workforce planning. The optimization and computational tools and techniques established include dynamic programming, constraint programming, genetic algorithms, statistical analysis, and discrete event simulation.Application of the proposed frameworks is demonstrated in a few contexts including optimization of employment, crew composition, and workload distribution in the real world cases. The findings confirm that integration of HR strategies with planning of construction activities not only result in positive impacts on HR development, but also on performance of a project through reduced employment cost, decreased duration, and increased daily throughput.